Abstract [en]

Objective: Frontal crashes still account for approximately half of all fatalities in passenger cars, despite several decades of crash-related research. For serious injuries in this crash mode, several authors have listed the thorax as the most important. Computer simulation provides an effective tool to study crashes and evaluate injury mechanisms, and using stochastic input data, whole populations of crashes can be studied. The aim of this study was to develop a generic buck model and to validate this model on a population of real-life frontal crashes in terms of the risk of rib fracture.

Method: The study was conducted in four phases. In the first phase, real-life validation data were derived by analyzing NASS/CDS data to find the relationship between injury risk and crash parameters. In addition, available statistical distributions for the parameters were collected. In the second phase, a generic parameterized finite element (FE) model of a vehicle interior was developed based on laser scans from the A2MAC1 database. In the third phase, model parameters that could not be found in the literature were estimated using reverse engineering based on NCAP tests. Finally, in the fourth phase, the stochastic FE model was used to simulate a population of real-life crashes, and the result was compared to the validation data from phase one.

Results: The stochastic FE simulation model overestimates the risk of rib fracture, more for young occupants and less for senior occupants. However, if the effect of underestimation of rib fractures in the NASS/CDS material is accounted for using statistical simulations, the risk of rib fracture based on the stochastic FE model matches the risk based on the NASS/CDS data for senior occupants.

Conclusion: The current version of the stochastic model can be used to evaluate new safety measures using a population of frontal crashes for senior occupants.

Iraeus, Johan

Abstract [en]

Introduction. Road traffic injuries are the eighth leading cause of death globally and the leading cause of death among young people aged 15-29. Of individuals killed or injured in road traffic injuries, a large group comprises occupants sustaining a thorax injury in frontal crashes. The elderly are particularly at risk, as they are more fragile. The evaluation of the frontal crash performance of new vehicles is normally based on barrier crash tests. Such tests are only representative of a small portion of real-life crashes, but it is not feasible to test vehicles in all real-life conditions. However, the rapid development of computers opens up possibilities for simulating whole populations of real-life crashes using so-called stochastic simulations. This opportunity leads to the aim of this thesis, which is to develop and validate a simplified, parameterized, stochastic vehicle simulation model for the evaluation of passive restraint systems in real-life frontal crashes with regard to rib fracture injuries.

Methods. The work was divided into five phases. In phase one, the geometry and properties of a finite element (FE) generic vehicle buck model were developed based on data from 14 vehicles. In the second phase, a human FE model was validated for oblique frontal crashes. This human FE model was then used to represent the vehicle occupant. In the third phase, vehicle buck boundary conditions were derived based on real-life crash data from the National Automotive Sampling System (NASS) and crash test data from the Insurance Institute for Highway Safety. In phase four, a validation reference was developed by creating risk curves for rib fracture in NASS real-life crashes. Next, these risk curves were compared to the risk of rib fractures computed using the generic vehicle buck model. In the final phase, injury mechanisms in nearside oblique frontal crashes were evaluated.

Results. In addition to an averaged geometry, parametric distributions for 27 vehicle and boundary condition parameters were developed as guiding properties for the stochastic model. Particular aspects of the boundary conditions such as pulse shape, pulse angle and pulse severity were analyzed in detail. The human FE model validation showed that the kinematics and rib fracture pattern in frontal oblique crashes were acceptable for this study. The validation of the complete FE generic vehicle buck model showed that the model overestimates the risk of rib fractures. However, if the reported under-prediction of rib fractures (50-70%) in the NASS data is accounted for using statistical simulations, the generic vehicle buck model accurately predicts injury risk for senior (70-year-old) occupants. The chest injury mechanisms in nearside oblique frontal crashes were found to be a combination of (I) belt and airbag loading and (II) the chest impacting the side structure. The debut of the second mechanism was found for pulse angles of about 30 degrees.

Conclusion. A parameterized FE generic passenger vehicle buck model has been created and validated on a population of real life crashes in terms of rib fracture risk. With the current validation status, this model provides the possibility of developing and evaluating new passive safety systems for fragile senior occupants. Further, an injury mechanism responsible for the increased number of outboard rib fractures seen in small overlap and near-side oblique frontal impacts has been proposed and analyzed.